Simplified version of white wine grape berries detector based on SVM and HOG features

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F16%3A39901144" target="_blank" >RIV/00216275:25530/16:39901144 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-33625-1_4" target="_blank" >http://dx.doi.org/10.1007/978-3-319-33625-1_4</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-33625-1_4" target="_blank" >10.1007/978-3-319-33625-1_4</a>

Result language
angličtina
Original language name
Simplified version of white wine grape berries detector based on SVM and HOG features
Original language description
The detection of grapes in real scene images is a serious task solved by researches dealing with precision viticulture. Our research has shown that in the case of white wine varieties, grape berry detectors based on a support vector machine classifier in combination with a HOG descriptor are very efficient. In this paper, simplified versions of our original solutions are introduced. Our research showed that skipping contrast normalization by image preprocessing accelerates the detection process; however, the performance of the detectors is not negatively influenced by this modification.
Czech name
—
Czech description
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Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Artificial Intelligence Perspectives in Intelligent Systems : Proceedings of the 5th Computer Science On-line Conference 2016 (CSOC2016). Vol 1
ISBN
978-3-319-33625-1
ISSN
2194-5357
e-ISSN
—
Number of pages
10
Pages from-to
35-45
Publisher name
Springer International Publishing AG
Place of publication
Cham
Event location
Zlín
Event date
Apr 26, 2016
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
000385237600004

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